Learning to Optimize

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Overview

Learning to Optimize studies how data can improve the algorithms and decisions used to solve optimization problems, especially when similar problems recur or standard solvers are costly. Approaches include meta-learning and reinforcement learning for update rules and optimizer selection, unrolled or differentiable methods such as learned ADMM, and learned heuristics or warm starts for mixed-integer and other solvers. These methods are used in settings ranging from neural-network training and black-box search to scheduling, power systems, and model predictive control, with work increasingly combining fast learned predictions with exact optimization or explicit feasibility checks. A central tension is whether methods trained on particular instances can generalize reliably to new problems while preserving solution quality, constraint satisfaction, and the computational guarantees of classical solvers.

Latest papers

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139 papers27 papers in the last four weeks, up 125% on the four weeks before. 0.2% of all new papers.

  1. WCC: A Learning-Based Framework for Deciding When to Apply Cooperative Coevolution in Large-Scale Optimization

    Oct 27, 2026Wenjie Qiu, Hepei Li, Jianfeng Wang +2Global OptimizationEvolutionary Optimization

    School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China · Taiyuan University of Technology, Taiyuan 030024, China · Nankai University, Tianjin 300350, China, and also with Hanyang University ERICA, Ansan 15588, South Korea

  2. Less is more: learning what to profile for GPU kernel optimization

    Oct 27, 2026Yihan Wang, Peiyu Liu, Runyu Chen +1GPU Kernel OptimizationLarge Language Model-Guided Optimization

    Renmin University of China · University of International Business and Economics

  3. AHEAD: Adaptive Neural Acceleration for Large-Scale Linear Programming

    Oct 26, 2026Sihao Liu, Zhichao Hou, Huayue Gu +4Learning to OptimizeLinear Programming

    North Carolina State University · Kennesaw State University · Nokia Applied Research

  4. Reactive Optimizers

    Oct 24, 2026Xingjian Bai, Jia-Hao Liang, Jayden Teoh +1Neural Network OptimizationLarge Language Model-Guided Optimization

    Massachusetts Institute of Technology

  5. Multiplicative vs. Additive State Coupling in Learned Optimizer Schedules

    Oct 23, 2026M. Harper Langston, Pierre-David Letourneau, Dalton Jones +7Learning to OptimizeOOD Generalization

    Qualcomm AI Research

  6. RSI-Opt: Recursive Self-Improvement Optimizer Agents For Model Training

    Oct 23, 2026Binghang Lu, Yige Sun, Guang LinLarge Language Model-Guided OptimizationLearning to Optimize

    Purdue University · Independent Researcher

  7. Preventing Model Extraction in Contextual Linear Optimization

    Oct 21, 2026Adam N. Elmachtoub, Tianyi Lin, Wenxuan LiuModel Extraction AttacksPredict-Then-Optimize

    Columbia University

  8. Self-Supervised Tuning of Low-Fidelity Optimization Models via High-Fidelity Feedback

    Oct 20, 2026Gonzalo E. Constante-Flores, André H. Quisaguano-Paredes, Asha Ramanujam +2Learning to OptimizeMulti-Fidelity Optimization

    Department of Electrical, Computer & Energy Engineering, University of Colorado Boulder · Davidson School of Chemical Engineering, Purdue University · ExxonMobil Technology and Engineering Company

  9. Learning SOCP Solver Dynamics with Graph Neural Networks

    Oct 19, 2026Adam Ghalem, Lou Salaün, Davide Rinaldi +1Second-Order Cone ProgrammingLearning to Optimize

    Université Paris-Saclay, CentraleSupélec, Inria · Nokia Bell Labs

  10. Reinforcement learning on the EPRI AI-ccelerating Unit Commitment benchmark: diagnosing over-commitment and guiding MILP with learned policies

    Oct 18, 2026Maharani Devira Pramita, Aidan O'SullivanLearning to OptimizeRL for Combinatorial Optimization

    UCL Energy Institute, Bartlett School of Environment, Energy and Resources, University College London, Central House, 14 Upper Woburn Place, London WC1H 0NN, United Kingdom

  11. Learning angles for quantum approximate optimization

    Oct 16, 2026Johannes Jakubik, Isabelle Wittmann, Zaheed Gaffoor +5Quantum Approximate Optimization AlgorithmLearning to Optimize

    IBM Research

  12. Algorithm Modelization: Transforming Optimization Algorithms into Evolvable Intelligence

    Oct 16, 2026Jian Yao, Zhiyao Zhang, Yichen Li +2Learning to OptimizeAlgorithmic Generalization

    Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong SAR, China.

  13. BOLT: Multi-Bottleneck Bound-Guided Learning for Flexible Job-Shop Scheduling with Time Lags and Resource-Coupled Transport

    Oct 15, 2026Ziheng Zhang, Wei Zhang, Yunyi Zhao +3Flexible Job Shop SchedulingLearning to Optimize

    Infocomm Technology Cluster, Singapore Institute of Technology, Singapore 828608 · College of Smart Energy, Shanghai Jiao Tong University, Shanghai, China · School of Computer Science and Informatics, Cardiff University, Cardiff CF24 4AG, U.K. +1

  14. Imperfect Is Perfect: Learned Column Prefilling for Branch-Price-and-Cut

    Oct 14, 2026Haoran Liu, Yu YangLearning to OptimizeMixed-Integer Linear Programming

    Department of Industrial Systems Engineering, University of Florida, Florida, United States

  15. Learning Warm Starts for the Simplex Method from Measured Solver Cost

    Oct 14, 2026Felix Parker, Danielle A. Ripsman, Emmett Springer +1Linear ProgrammingLearning to Optimize

    Center for Systems Science and Engineering, Johns Hopkins University

  16. Robust Explanatory Analysis for Structured Optimization Networks (REASON) in Learning

    Oct 14, 2026Vahid Jebraeeli, Hamid Krim, Keisuke FujiiInference-Time OptimizationNeural Network Robustness

    ECE Department, North Carolina State University, Raleigh, NC, USA · Graduate School of Informatics, Nagoya University, Nagoya, Japan

  17. Learning to Design Convex Relaxations for Nonconvex Optimization

    Oct 12, 2026Jinrun Liu, Bai Yan, Tengfei Liu +5Convex RelaxationNonconvex Optimization

    Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China · School of Computer Science and Technology, Dongguan University of Technology, Dongguan 523808, China · School of Artificial Intelligence and Computer Science, Shaanxi Normal University, Xi’an 710119, China

  18. Full Waveform Inversion with a Learned Preconditioner

    Oct 11, 2026Jeongjin ParkSeismic ImagingInverse Problems

  19. MoSAIC: Learning DAG Scheduling Heuristics from Optimal Schedules through Motif-Aware Recovery and LLM-Guided Reasoning

    Oct 10, 2026Shiva Ahir, Hashmath Shaik, Alex Doboli +2Automated Heuristic DesignLearning to Optimize

    Department of Electrical & Computer Engineering, Stony Brook University, New York, United States of America · Barcelona Supercomputing Center, Barcelona, Catalonia, Spain · Department of Computer Science, Hofstra University, New York, United States of America

  20. Sequence-Structured Decision Learning for Branch-and-Bound in Mixed-Integer Linear Programming

    Oct 10, 2026Tengfei Liu, Jinrun Liu, Bai Yan +2Branch and BoundMixed-Integer Linear Programming

    Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China · School of Computer Science and Technology, Dongguan University of Technology, Dongguan, China

  21. A Scalable Learned Iterative Solver for Nonlinear MPC via Temporal Decomposition

    Oct 9, 2026Lukas Lüken, Sergio LuciaLearning to OptimizeNonlinear MPC

    Chair of Process Automation Systems, TU Dortmund University, Emil-Figge Straße 70, Dortmund, 44227, North Rhine-Westphalia, Germany

  22. AI-Driven, Timing-Aware Power Optimization

    Oct 8, 2026Amit SharmaElectronic Design AutomationLearning to Optimize

    IEEE Member

  23. ORDO: Operation-level Round-aware Dynamic Ordering for MIP Presolve

    Oct 8, 2026Zehuan Chen, Chunhe SongMixed-Integer Linear ProgrammingOperations Research

    Institute of Industrial Artificial Intelligence, CAS

  24. Outperformance Inverse Optimization: Learning Objective Functions that Outperform Agent Decisions

    Oct 7, 2026Akira KitaokaLearning to OptimizeMixed-Integer Linear Programming

  25. Lightweight and Versatile Learned Optimization by Recombination of Gradient History

    Oct 7, 2026Minyoung Choi, Dalta Imam Maulana, Wanyeong JungLearning to Optimize

    KAIST Daejeon, Republic of Korea

  26. A Decision-Focused Neural Optimization Framework for Personalized Route Reproduction from Vehicle Trajectories

    Oct 6, 2026Gyeongjun Kim, Yeseul Kang, Keemin SohnLearning to OptimizeCombinatorial Optimization

    Department of Smart City, Chung-Ang University, Seoul, Korea · Department of Urban Engineering, Chung-Ang University, Seoul, Korea · Department of Urban Engineering, Department of Smart City, Chung-Ang University, Seoul, Korea

  27. An overview of machine learning-enhanced iterative methods for systems of linear and nonlinear equations

    Oct 5, 2026Yuhuang Meng, Jing Zhao, Alexander HeinleinLearning to OptimizeScientific ML

    Delft Institute of Applied Mathematics, Delft University of Technology, Mekelweg 4, Delft, 2628 CD, the Netherlands · Department of Hydrodynamics and Forecasting, Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands

  28. ML-OPF-Bench: Benchmarking Machine Learning for Optimal Power Flow

    Oct 3, 2026Xinyi Liu, Xuan He, Danny H. K. Tsang +1Optimal Power FlowLearning to Optimize

    Dartmouth College · Hong Kong University of Science and Technology (Guangzhou) · University of Alberta

  29. Learned Preconditioning for a Primal-Dual Interior-Point Method

    Sep 28, 2026Abhinav Madabhushi, Jialin Liu, Minxin ZhangPrimal-Dual OptimizationLearning to Optimize

    Department of Mathematics, University of California, Los Angeles · School of Data, Mathematical, and Statistical Sciences, University of Central Florida

  30. SOLAR: A State-Driven Online Learning Rate Scheduler for LLM Pretraining

    Sep 28, 2026Qiulin Shang, Binyu Wang, Yongqi Qiao +3Language Model PretrainingLearning Rate Scheduling

    Peking University · Nanjing University